Business-to-business (B2B) companies spend significant time and resources to retain existing customers and expand wallet share within those existing customers. In their marketing, sales, maintenance and support and other interactions with customers, businesses create, gather and store large volumes of business transaction data such as company's line level transaction history—each and every customer order, product by product, and account by account, that is captured and stored over some period of time. With the advances in data storage and data mining technologies as well as customer relationship management technologies, businesses increasingly seek to use this often voluminous business transaction data for the purposes of retaining and expanding wallet share within existing customers. Businesses know that business transaction data holds a wealth of knowledge and insight. Yet most companies are challenged to consistently and systematically transform that data into an actionable form that drives measurable business results because traditional analytical and reporting methods lack the required statistical and predictive rigor to product high quality customer retention and wallet share expansion insights.
To extract significant value, the business must be able to find customer retention and wallet share expansion insights in their business transaction data beyond what they can observe with the naked eye. For example, the business likely knows how much each of their best customers spends with them. They may even know how much the customers spend in each product category and if that spend changes over time. But they are not likely to know which products their customers are willing and able to buy from them, but are buying elsewhere (wallet share expansion opportunity) or which customers are starting to defect to their competitors (retention opportunity) which results in lost sales for the business.
Identifying wallet share expansion opportunity requires the ability to predict what customers are not buying, but could be buying from the business and in what quantities. Business transaction data can reveal wallet share expansion opportunities, just not in its raw form. The data needs to be processed, analyzed and presented in the right way for the business to see the opportunities. This is done by intelligently grouping customers with common purchase behavior across a range of products and product groups through rigorous analysis using advanced statistical techniques. The resulting customer groups are used to generate purchase pattern profiles, which enable businesses to spot opportunities that are not visible in simple statistical analysis.
Identifying customer retention opportunity requires the ability to quickly detect significant deviations in customer purchase patterns. Business transaction data can be used to reveal retention opportunities; however the business transaction data in its raw form doesn't reveal these opportunities. The data needs to be processed, analyzed and presented in the right way for the business to see the opportunities. A more sophisticated level of rigor and scientific accuracy is needed to transform the data into actionable purchase patterns. Customer retention opportunities are identified by establishing a profile of normal customer purchase behavior, across products and product groups, during a baseline period and detecting significant deviations during an evaluation period. The definition of normal customer purchase behavior is multivariate, considering frequency, size and regularity of purchase.
This kind of insight can help businesses plan sales, marketing and product strategies to boost revenue including:
1. Growth through Cross-Selling
2. Identification of Lost Sales
3. Preempting Customer Defection and Churn
4. Data-Driven Territory Planning
5. Moving Inventory
6. Recognizing Sales Upticks
7. New Product Introduction